Name
Abstract | ||
|---|---|---|
Efficient query answering over ontologies is one of the most useful and important services to support Semantic Web appli- cations. Approximation has been identified as a potential way to reduce the complexity of query answering over OWL DL ontologies. Existing approaches are mainly based on syntac- tic approximation of ontological axioms and queries. In this paper, we propose to recast the idea of knowledge compila- tion into approximating OWL DL ontologies with DL-Lite ontologies, against which query answering has only poly- nomial data complexity. We identify a useful category of queries for which our approach guarantees also complete- ness. Furthermore, this paper reports on the implementa- tion of our approach in the ONTOSEARCH2 system and pre- liminary, but encouraging, benchmark results which compare ONTOSEARCH2's response times on a number of queries with those of existing ontology reasoning systems. |
Year | Venue | Keywords |
|---|---|---|
2007 | AAAI | ontosearch2 system,polynomial data complexity,useful category,approximating owl-dl ontology,approximating owl dl ontology,syntactic approximation,efficient query answering,owl dl ontology,paper report,query answering,dl-lite ontology,semantic web |
Field | DocType | Citations |
Ontology (information science),Ontology,Polynomial,Information retrieval,Computer science,Axiom,Semantic Web,Knowledge compilation,Syntax,Completeness (statistics) | Conference | 37 |
PageRank | References | Authors |
1.79 | 16 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jeff Z. Pan | 1 | 2218 | 158.01 |
| Edward Thomas | 2 | 171 | 9.54 |